Agent Mode by Receiptor AI - Bookkeeping assistant that runs receipt workflows end-to-end
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Receiptor AI is an agentic bookkeeping assistant that runs your receipt workflow end-to-end: it collects receipts from your inbox and your mobile, organizes them in your cloud or accounting software, and matches them to your bank transactions.
It works quietly in the background with 99% accuracy, and only asks questions when it needs more context. The result: clean books and organized receipt data you can query from anywhere: the app, WhatsApp, or right inside Claude and ChatGPT.
Replies
Bookkeeping that runs itself is the dream for solo
founders. The amount of time spent manually
categorising receipts and reconciling accounts is
embarrassing when you think about it. If Receiptor
genuinely handles this autonomously that's a
significant time unlock. Following closely 👍
Receiptor AI
@aditya_kalkotwar Hey Aditya! Actually, it started with a solopreneur for its own receipt and bookkeeping challenge. So I get you! I'm happy to get your feedback when you test it. Thanks!
Auto-posting to Xero/QBO is the bold part. The edge cases that bit us when we built similar classifiers were refunds, partial payments, and split transactions, where the model is confident and wrong and someone only catches it at reconciliation weeks later. Do you bias toward precision and route the ambiguous ones to a review queue rather than chase full automation from day one? The reversal cost on a bad post tends to dwarf the time it saved.
Receiptor AI
@dipankar_sarkar We do bias toward precision over recall. Anything the model isn't confident on goes to a review queue rather than posting automatically, because you're right: the reversal cost is rarely worth it. We're not chasing full automation from day one, we're chasing the right automation with a clear audit trail so when something does go wrong, it's obvious and fixable fast. Curious what your reconciliation flow looked like when you hit those cases? always learning here
the "asks once, never asks twice" design is the right call - most agentic tools interrupt constantly and the interruptions kill user trust fast. curious about the pattern recognition piece: how many transactions does it take before it's confident enough to categorize correctly on its own? and what happens when a categorization error from 6 months ago surfaces at tax time - does the agent know it was wrong, or does the user eat it?
Receiptor AI
@galdayan On pattern recognition, 99% of the time it'll categorize your expense correctly on the first attempt, using just the Chart of Accounts you've defined (the more context you add here, the better).
If you have to manually edit a transaction's categorization, it'll take ~2-4 iterations for the agent to learn the rule and apply it with confidence next time. Simpler patterns, like a recurring SaaS subscription, click faster. Ambiguous ones, like a vendor that sometimes bills for travel and sometimes for services, stay in review longer on purpose.
For error flagging, the agent can either 1) flag a document to be reviewed if it doubts certain fields (categorization, date, amounts, etc.) or 2) ask for context to decide on the correct categorization. At any time, you can request that your documents be retroactively reclassified.
ChatWebby AI
The "self-healing, math-validated extraction" detail is the part that stands out to me — most receipt tools just OCR and hope, so having the agent catch its own arithmetic errors is a smart trust signal for something running unattended. When it does correct itself or reclassify, does that correction become part of the audit trail you can show an auditor, or does the document just quietly end up in its final state?
Receiptor AI
@zain_sheikh The math validation and reclassification are internal, so the document just arrives in its final clean state rather than showing every correction step. The audit trail is at the workflow level: which emails were scanned, which documents were extracted, where they were exported, and when.
Build Check
Cool Romeo! It's sounds super interesting. Wish you all the best on this impressive launch!
Receiptor AI
@german_merlo1 Thanks German! I hope you'll appreciate it
The bookkeeping-on-autopilot angle is easy to understand from the tagline. For teams looking at Receiptor AI from the Accounting or Productivity side, where does the human review usually happen? Is the product meant to fully automate receipt handling, or more to prepare the bookkeeping work so someone can approve it faster?
Receiptor AI
@mia_qiao Good question. Once you've invited your team or accountant to the workspace, the first natural review point is at the document layer: anything the agent flags as ambiguous or needing context on surfaces there before moving forward.
Some users also set up their own labels early on to match their approval workflow and manually review before it exports to QuickBooks, Xero, or their cloud. Full automation is the goal, but we know that trust takes time to build, so a human-in-the-loop approach is always an option. And the more you use it upfront, the faster it learns your specific setup and the less you'll need to touch it.
What would be best in your case?
I wonder where Receiptor AI draws the line between automation and user review？In accounting, confidence and auditability matter a lot, even when AI agents are doing the repetitive parts. Is the intended flow more like fully automated bookkeeping, or does it surface suggested actions for someone to approve before things get finalized?
Receiptor AI
@crystalmei The line is yours to draw. By default, the agent runs the full workflow automatically, but every action is logged and nothing posts to your accounting software without you being comfortable with it. Most users start by reviewing everything, build confidence over time, and gradually let it run on its own. The audit trail is always there either way, so auditability isn't dependent on how much you automate.
How is your current workflow?
bookkeeping is one of those workflows where AI automation actually makes sense because the rules are well defined and the cost of doing it manually is way too high for small teams. the auto-categorization is the key part. how accurate is it out of the box or does it need a few weeks of corrections before it learns your patterns? that initial training period is usually where people give up on automation tools.
Receiptor AI
@shubham4real Honestly, out of the box accuracy is high enough that most users don't hit that painful correction period at all. It pulls from your Chart of Accounts from day one, so as long as that's reasonably defined, categorization is solid from the first transaction. The few cases where it gets it wrong, it either flags for review or asks for context rather than guessing, so errors don't pile up quietly. And if something does slip through, you can retroactively reclassify everything in bulk.
Receiptor AI
@shubham4real what's your experience with similar tools?
The Receiptor interface keeps getting better. I've always HATED the feel of receipt tracking, organizing and double entry accounting software generally. It's like factory piecework. Talking/Texting in natural language, follow through via what's app, hooking it up to do a big sweep through all my channels makes me feel like I have an assistant who doesn't have any personal complications. So good! I wouldn't say I look forward to bookkeeping quite yet- BUT almost! I love seeing this product evolve, and most importantly- creatively designing new processes for myself. Am I almost at the point where I can say, I enjoy bookkeeping?? Because that would be a crazy statement coming from me. Ha. Lets Go!
Receiptor AI
@zoecoombes "An assistant who doesn't have any personal complications" might be the best description of Receiptor we've ever heard. We're putting that on a t-shirt.
Thanks so much Zoe!! You're closer than you think, the day you stop dreading it is the day we know we got it right. Let's go 🚀
The Claude/ChatGPT query surface is the bit I would keep separate from the bookkeeping write path. Reading receipt history and asking “what did I spend on travel?” is one trust level; auto-categorizing or syncing to Xero/QBO is another.
For an SMB user I’d want the assistant to show when a chat answer is read-only, when it is proposing a bookkeeping change, and what exact document/bank transaction would be touched before it writes. That distinction would make the “only asks when unsure” claim much easier to trust.
Receiptor AI
@tang_weigang Completely agree on the distinction. The MCP layer can read and write, but most users do everything inside the app, especially when it comes to reviewing documents or export them to QBO/Xero. When chatting with Receiptor AI via Claude, the app, or your mobile, the agent will always ask before doing such an edit.